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Will it be forbidden to drive a car yourself at some point?

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Drag the boxes onto the matching gaps.

Farming is as old as itself, but with industrialization, modern agriculture grew in scale and sophistication to degrees never seen before in history, especially during the of the 1950s-60s. The sector may be poised to go through another comparable evolutionary step with machines doing important jobs in the fields.

The COVID-19 pandemic also shed further light on the importance of maintaining supply under the most difficult , particularly when labour shortages become a global, rather than a local, problem.

That was what researchers at Harper Adams University thought while running an experimental farm called Hands Free Hectare in the British village of Edgmond in 2016. It started with one (2.47 acres) using a converted tractor and 25-year-old combine into autonomous vehicles equipped with .

Agriculture experts generally agree that making this a reality on a grand scale will require commitments from several players. For starters, the world's largest agriculture equipment manufacturers would not only need to embrace developing autonomous machines but also the AI technology smaller developers are working on to make them smarter.

That includes the likes of John Deere, AGCO, Iseki and Kubota, among others. For its part, John Deere unveiled a prototype self-driving tractor and autonomous sprayer in October 2019 that offered a glimpse into how machines may handle more of the grunt work required for harvesting crops.

Blue River Technology, acquired by John Deere in 2017, created See and Spray, a device that uses cameras, machine learning and AI to detect weeds in their fields. The machine has the ability to spray pesticides, and fungicides. This technology can help farmers reduce the amount of weeds among their crops as much as 90 percent in a few years, but in order to be effective, it requires ultra low- to quickly determine which plants are weeds and take action. This is where will make a difference.

Projections vary, especially when delineated into segments, but overall, put the farming equipment market at $180 billion by 2024 in a report from Global Market Insights released in October 2019.

In lieu of new vehicles, engineers and developers could convert existing tractors into robotic ones. Several firms, like Precision Makers in the Netherlands, have offered that kind of technology before, though it is more focused on a "cab-less" robot tractor called the Greenbot that it's now building for John Deere. The market, at large, is also veering toward full autonomy, albeit still years away from mass adoption.

Machines could be a major cog in that wheel in improving to a much higher degree. Farmers may gain the ability to more accurately spread fertilizer and herbicides, or apply what is necessary only to the crops that need it most, rather than all of them. Using a combination of GPS, sensors, and imaging, they would presumably have a better handle on how to the robotic vehicles tilling the land.

It's a futuristic vision, but one that looks to become a reality in this decade. Self-driving cars on the road may get plenty of attention, but it may be the ones on the farms that keep everyone fed.

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Drag the boxes onto the matching gaps. Farming is as old as itself, but with industrialization, modern agriculture grew in scale and sophistication to degrees never seen before in history, especially during the of the 1950s-60s. The sector may be poised to go through another comparable evolutionary step with machines doing important jobs in the fields.

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Knoword is a fast-paced word game that challenges your vocabulary, tests your typing skills, and stimulates your mind.

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Do autonomous cars actually have to go to the MOT more often? And do they go there themselves?

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Would you feel safe as passenger in a fully autonomous car?

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Autonomous and connected vehicles are expected to improve traffic flow and safety, but they also represent a new target for cybercriminals. The growing complexity of software and communication interfaces makes connected and autonomous cars more vulnerable to attacks. Cybersecurity breaches result in a loss of data privacy, negatively impact car safety and even cause accidents. Therefore, appropriate safety measures and effective and robust cybersecurity solutions are essential.

6 Security Risks That Threaten Autonomous and Connected Vehicles

Autonomous vehicles communicate with other vehicles and infrastructure via external networks that can be exploited by hackers. Autonomous vehicles process a lot of information, such as image related data from deep learning algorithms. Large amounts of data are prone to adversarial attacks and increased false positives. Below, you'll find a review of the most common attacks that threaten connected and autonomous vehicles.
1. Attacks on Smart Remote Keys
Passcodes and remote keys are based on Infrared Radiation (IR) and Bluetooth technologies. Hackers can crack IR communication easily with a brute force attack and manipulate Bluetooth connectivity to leak private information.
2. Attacks on Cloud-Based Networks
Self-driving vehicles process large volumes of data that are stored in the cloud. Sending and receiving data from the cloud is a security vulnerability because attackers can compromise data centers. Threat actors exploit data center breaches to access sensitive information such as vehicle safety features.
3. Malware Attacks-Software Security
Software security is an important factor in vehicle safety. Automotive manufacturers are facing the same security challenges as any other software organization. The most common factors that render software security are the pressure to meet deadlines, coding errors, lack of education on secure coding practices, and lack of vulnerability testing in production.
4. Sensors
Autonomous vehicles are equipped with a range of sensors that help them navigate roads, detect other vehicles on the road, stop for pedestrians, and handle any unexpected dangers. Each type of sensor has its own strengths and weaknesses in terms of range, detection capabilities, and reliability. Sensors like cameras, LiDAR and GPS are vulnerable to the security threats explored below.

Autonomous vehicles use GPS data to locate and navigate the vehicle with great accuracy. Data from GPS satellites in the public domain can be easily accessed by anyone. Hackers can manipulate GPS data to provide wrong directions or to control the routing of the vehicle. This leads to security and safety issues of passengers. Manipulation of GPS signals is known as GPS spoofing and jamming.

Light Detection and Ranging (LiDAR) is used to localize the environment, detect and avoid obstacles. LiDAR technology measures the time it takes for light to travel to and from the vehicle. The measured times determine the distance to the object location. Hackers can send a signal of the same frequency to the LiDAR scanner and manipulate the object location. The vehicle may think that an object is nearby and stop, when in reality the object is far away.

Inertial Measurement Unit (IMU) is an electronic device that measures the velocity, acceleration, and orientation of the vehicle. IMU also monitors dynamic environmental changes like the steepness of a road. Malicious modification of IMU data causes false-positive recognition of road steepness. Attackers can force the vehicle move slowly on steep roads, thus slowing down the entire traffic flow.
5. Network Attacks
A network attack is a method used to maliciously compromise network security. Every endpoint in the network is a part of the network attack surface. Hackers deploy malware and advanced persistent threats (APTs) on endpoints, for the purpose of gaining access to a network. Usually a network is exploited through remote access Wi-Fi and even local area networks (LANs).

Vehicle to everything (V2X) communication is a technology that enables data exchange between a connected vehicle and other cars and infrastructure. Attackers exploit this type of communication to expose the network access points.

Communicating channels between a car and external devices like smartphones are established through Wii, Bluetooth and GSM protocols. These protocols are inherently vulnerable and contain known bugs, which attackers can exploit.

The main goal of V2V networks is to prevent accidents by opening a channel of communication between vehicles. Connected vehicles use the V2V network to transmit information about speed, location, travel route, braking, and loss of stability.

The major drawback of V2V communication is the use of insecure and unencrypted protocols that enables attackers to eavesdrop the traffic between vehicles. For example, when attackers launch an Impersonation attack, they deploy a malicious car that connects to the host vehicle. After establishing communication, the false car sends malicious code and receives sensitive information like authentication keys.

Autonomous vehicles use V2I to communicate with surrounding infrastructure systems, such as intelligent traffic signs and lights, and cellular network nodes. An attacker can easily gain access to a vehicle network and ECUs through such communication.
6. APT Attacks
ECU is an electronic control module for sensors and actuators in a vehicle. A typical vehicle consists of more than 100 ECUs. The proprietary code inside the ECU makes it safe and secure.

Attackers can update the ECU with malicious firmware and manipulate its state and actions using the external interface. They modify the ECU memory and security keys using hashing techniques and authentication of software updates. Such attacks are referred to as a direct access attack, because the attacker has direct physical access to the ECU.

Onboard diagnostics (OBD) and OBD port are present in almost all manufactured vehicles since 2008. OBD ports collect diagnostic data of vehicles. This data contains information about vehicle faults and performance.

OBD interacts with the ECU's communicating through CAN bus. It is an external device like USB which has to be connected to the vehicle through a port. Once connected, the OBD port sends and receives data to and from the vehicle ECU's. Hackers can then exploit and manipulate the transferred data and inject malicious code into the vehicle network.

Conclusion

Autonomous car security vulnerabilities are far more dangerous than malicious emails or even stolen credit card numbers. Malicious code exploits can cause real physical harm to a driverless car passenger. Rogue nations and terrorists looking to cause chaos and damage to infrastructure can also exploit these vulnerabilities.

It may take a long time for the automotive industry to ensure maximum security in autonomous vehicles. There is no doubt that hackers will attempt to breach self-driving cars, but today's cybersecurity professionals have more powerful tactics to defend against them.
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Top Security Risks That Threaten Autonomous and Connected Vehicles | HERE Mobility Blog

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Autonomous and connected vehicles are expected to improve traffic flow and safety, but they also represent a new target for cybercriminals. The growing complexity of software and communication interfaces makes connected and autonomous cars more vulnerable to attacks. Cybersecurity breaches result in a loss of data privacy, negatively impact car safety and even cause accidents.

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Which newspaper published the article?, What is the first subject in the article?, What hurdle is mentioned that delays the arrival of autonomous cars?

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Join a game of kahoot here. Kahoot! is a free game-based learning platform that makes it fun to learn – any subject, in any language, on any device, for all ages!

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The ethical dilemma of self-driving cars - Patrick Lin

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Ford and other companies say the industry overestimated the arrival of autonomous vehicles, which still struggle to anticipate what other drivers and pedestrians will do.

Argo AI's self-driving technology will be used by Ford and Volkswagen in ride-sharing services. Credit... Jeff Swensen for The New York Times

A year ago, Detroit and Silicon Valley had visions of putting thousands of self-driving taxis on the road in 2019, ushering in an age of driverless cars.

Most of those cars have yet to arrive - and it is likely to be years before they do. Several carmakers and technology companies have concluded that making autonomous vehicles is going to be harder, slower and costlier than they thought.

"We overestimated the arrival of autonomous vehicles," Ford's chief executive, Jim Hackett, said at the Detroit Economic Club in April.

In the most recent sign of the scramble to regroup, Ford and Volkswagen said Friday that they were teaming up to tackle the self-driving challenge.

The two automakers plan to use autonomous-vehicle technology from a Pittsburgh start-up, Argo AI, in ride-sharing services in a few urban zones as early as 2021. But Argo's chief executive, Bryan Salesky, said the industry's bigger promise of creating driverless cars that could go anywhere was "way in the future."

He and others attribute the delay to something as obvious as it is stubborn: human behavior.

Researchers at Argo say the cars they are testing in Pittsburgh and Miami have to navigate unexpected situations every day. Recently, one of the company's cars encountered a bicyclist riding the wrong way down a busy street between other vehicles. Another Argo test car came across a street sweeper that suddenly turned a giant circle in an intersection, touching all four corners and crossing lanes of traffic that had the green light.

"You see all kinds of crazy things on the road, and it turns out they're not all that infrequent, but you have to be able to handle all of them," Mr. Salesky said. "With radar and high-resolution cameras and all the computing power we have, we can detect and identify the objects on a street. The hard part is anticipating what they're going to do next."

Mr. Salesky said Argo and many competitors had developed about 80 percent of the technology needed to put self-driving cars into routine use - the radar, cameras and other sensors that can identify objects far down roads and highways. But the remaining 20 percent, including developing software that can reliably anticipate what other drivers, pedestrians and cyclists are going to do, will be much more difficult, he said.

A year ago, many industry executives exuded much greater certainty. They thought that their engineers had solved the most vexing technical problems and promised that self-driving cars would be shuttling people around town in at least several cities by sometime this year.

Waymo, which is owned by Google's parent company, Alphabet, announced that it would buy up to 62,000 Chrysler minivans and 20,000 Jaguar electric cars for its ride service, which operates in the Phoenix suburbs. General Motors announced that it would also start a taxi service by the end of this year with vehicles, developed by its Cruise division, that have no steering wheels or pedals.

Captivated by the notion of disrupting the transportation system, deep-pocketed investors rushed to get a piece of the action. Honda and the Japanese tech giant SoftBank invested in Cruise. Amazon, which hopes to deliver goods to its shoppers by driverless vehicles, invested in Aurora, another start-up in this area.

"There was this incredible optimism," said Sam Abuelsamid, an analyst at Navigant Research. "Companies thought this was a very straightforward problem. You just throw in some sensors and artificial intelligence, and it would be easy to do."

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A Waymo autonomous vehicle in December in Chandler, Ariz. The company has a fleet of about 600 test vehicles, about as many as it had last year. Credit... Caitlin O'Hara for The New York Times

The industry's unbridled confidence was quickly dented when a self-driving car being tested by Uber hit and killed a woman walking a bicycle across a street last year in Tempe, Ariz. A safety driver was at the wheel of the vehicle, but was watching a TV show on her phone just before the crash, according to the Tempe Police Department.

Since that fatality, "almost everybody has reset their expectations," Mr. Abuelsamid said. It was believed to be the first pedestrian death involving a self-driving vehicle. Elsewhere in the United States, three Tesla drivers have died in crashes that occurred while the company's Autopilot driver-assistance system was engaged and both it and the drivers failed to detect and react to hazards.

Companies like Waymo and G.M. now say they still expect to roll out thousands of self-driving cars - but they are much more reluctant to say when that will happen.

Waymo operates a fleet of 600 test vehicles - the same number it had on the road a year ago. A portion of them are the first set of vehicles it will be buying through the agreements with Chrysler and Jaguar. The company said it expected to increase purchases as it expanded its ride service.

"We are able to do the driving task," Tekedra Mawakana, Waymo's chief external officer, said in an interview. "But the reason we don't have a service in 50 states is that we are still validating a host of elements related to offering a service. Offering a service is very different than building a technology."

G.M. declined to say if it was still on track to start a ride service "at scale" this year, as it originally planned. Its chief executive, Mary Barra, told analysts in June that Cruise was moving "at a very aggressive pace" without saying when commercial operations would begin.

China, which has the world's largest auto market and is investing heavily in electric vehicles, is trailing in development of self-driving cars, analysts say. The country allows automakers to test such cars on public roads in only a handful of cities. One leading Chinese company working on autonomous technology, Baidu, is doing much of its research at a lab in Silicon Valley.

Tesla and its chief executive, Elon Musk, are nearly alone in predicting widespread use of self-driving cars within the next year. In April, Mr. Musk said Tesla would have as many as a million autonomous "robo taxis" by the end of 2020.

Tesla believes its new self-driving system, based on a computer chip it designed, and the data it gathers from Tesla cars now on the road will enable the company to start offering fully autonomous driving next year.

But many experts are very skeptical that Tesla can pull that off.

An Uber driverless car on a test drive in 2016 in San Francisco. Since one of the company's self-driving test cars hit and killed a pedestrian in Arizona last year, industry expectations have changed. Credit... Eric Risberg/Associated Press

Mr. Salesky said it was relatively easy to enable a car to see and identify obstacles on the road with the help of radar, cameras and lidar - a kind of radar that uses lasers - as well as the software and computing power to process images and data.

It's much more difficult to prepare self-driving cars for unusual circumstances - pedestrians crossing the road when cars have the green light, cars making illegal turns. Researchers call these "corner cases," although in city traffic they occur often.

"If you're out driving 20 hours a day, you have a lot of opportunities to see these things," Mr. Salesky said.

Equally challenging is teaching self-driving cars the finer points of driving, sometimes known as "micro maneuvers." If a vehicle ahead is moving slowly looking for a parking space, it is best to not follow too closely so the car has room to back into an open spot. Or to know that if a car is edging out into an intersection, it can be a sign the driver may dart out even if he doesn't have the right of way.

The technology is available now to create a car that won't hit anything. But such a car would constantly slam on the brakes.

"If the car is overly cautious, this becomes a nuisance," said Huei Peng, director of Mcity, an autonomous-vehicle research center at the University of Michigan.

Some companies argue that the way to get more self-driving vehicles on the road is by using them in controlled settings and situations. May Mobility operates autonomous shuttles in Detroit; Providence, R.I.; and Columbus, Ohio. These are not minivans or full-size cars but six-passenger golf carts. They travel short, defined routes at no more than 25 miles per hour. In many cases they provide public transportation where none is available.

"A vehicle that needs to go at higher speeds will need more expensive, more exotic sensors," said Alisyn Malek, the company's chief operating officer. "Using a low-speed vehicle makes the task of operating an autonomous vehicle easier, so we can use what works in the technology today."

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The company has been running six shuttles between the Providence train station and Olneyville, a growing neighborhood a few miles away, since May. The trial is backed by the Rhode Island Department of Transportation, which is paying May Mobility $800,000 for the first year of service. The company expects to take its service to Grand Rapids, Mich., this year, in a partnership led by the city. Based in Ann Arbor, Mich., May Mobility has raised $33 million from investors, including a $10 million round led by Toyota and BMW.

Also this year, a Boston start-up, Optimus Ride, plans to begin operating driverless shuttles at the Brooklyn Navy Yard that also travel at 25 m.p.h. or less.

Ms. Malek said she believed it would take years and perhaps even a decade or more to develop driverless cars that could travel anywhere, any time.

"Our focus is, how can we use the technology today?" she said. "We realize that today we have to start somewhere."

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Despite High Hopes, Self-Driving Cars Are 'Way in the Future' (Published 2019)

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Ford and other companies say the industry overestimated the arrival of autonomous vehicles, which still struggle to anticipate what other drivers and pedestrians will do. A year ago, Detroit and Silicon Valley had visions of putting thousands of self-driving taxis on the road in 2019, ushering in an age of driverless cars.